analogs.train: Analogs

In SantanderMetGroup/downscaleR: A climate4R package for statistical downscaling <http://meteo.unican.es/climate4r>

Analogs

Description

Analog method implementation

Usage

analogs.train(
  x,
  y,
  dates,
  n.analogs = 4,
  sel.fun = "mean",
  window = 7,
  n.random = NULL,
  pool = 0
)

Arguments

x	The grid data. Class: matrix.
y	The observations data. Class: matrix.
dates	Dates of the grid and observations data.
n.analogs	An integer. Number of analogs. Default is 4.
sel.fun	A string. Select a function to apply to the analogs selected for a given observation. Options are "mean", "wmean" (i.e., weighted mean), "max", "min", "median", "prcXX" (i.e., prc85 means the 85th percentile of the analogs values distribution). Default is "mean". the function applied to the analogs values, (i.e., sel.fun = c("mean","max","min","median","prcXX"), with default "mean") and the temporal window, (i.e., window = 0).
window	An integer. Window of days removed when selecting analogs. If window = 7, then 7 days after the observation date and the 7 days before the observation date are removed. Default is 0.
n.random	An integer. Choose N random analogs among the closest n.analogs. Default is NULL.
pool	An integer. Number of auxiliary analogs in case there are NaN or NA in the original analogs.

Details

The analogs actually is not a model in the sense that it is not really trained. The model would be the data where to search the analogs. For this reason this function only saves the information to search analogs in a list.

Value

A list containing the grid data, the observations and a list with information concerning the analogs.

Author(s)

J. Bano-Medina

SantanderMetGroup/downscaleR documentation built on July 4, 2023, 4:28 a.m.